Defect Recognition Algorithm Based on Curvelet Moment and Support Vector Machine
会议名称：《2010 International Conference on E-Health Networking, Digital Ecosystems and Technologies》
会议日期：2010年
学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 13[艺术学] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程]
基 金：supported by the Natural Science Foundation of Tianjin University of Science and Technology China (Grant No.20070211)
关 键 词：defect recognition curvelet moment support vector machine
摘 要：In this paper, a new recognition algorithm based on curvelet moment and support vector machine(SVM) is proposed for chip defect recognition. The proposed recognition method is implemented through a reference comparison method. First the defect regions of chips are extracted through preprocessing, and then the curvelet moment feature of the defect region is computed as the input of SVM classifier, the output of the trained SVM classifier is the result of defect recognition. The algorithm combines the good properties of curvelet moment and SVM classifier, the former can provide multi-scale, local details and orientation information of the defect region, and the latter is suitable to solve the small samples, nonlinear and high dimensions pattern recognition problem. Experimental results show that the algorithm has higher recognition rate compared with PCA based method and can solve the complex defects recognition problem effectively.